Differentiation between lymphomas and pseudolymphomas of the skin by computerized DNA-image cytometry

Differentiation between malignant and benign follicular adnexal tumours of the skin by DNA image cytometry

BACKGROUND

We have demonstrated in previous studies that DNA image cytometry (DNA ICM) can be helpful in detecting malignancy in sebaceous tumours of the Muir-Torre syndrome and sweat gland tumours. However, little is known about DNA ICM in cutaneous adnexal tumours with follicular differentiation.

OBJECTIVES

To study a larger series of benign and malignant follicular adnexal tumours with DNA ICM.

METHODS

We studied 13 malignant follicular tumours (seven trichilemmal carcinomas, five malignant proliferating pilar tumours, one pilomatrix carcinoma) and 55 benign follicular tumours (four tumours of the follicular infundibulum, seven Winer's pores, eight trichilemmomas, two trichofolliculomas, 16 trichoepitheliomas, 13 pilomatrixomas, five trichoblastomas) by DNA ICM. All cases were clear-cut as malignant or benign, respectively, on histopathological criteria. The stemline interpretation according to Böcking et al. (DNA distribution in gastric cancer and dysplasia. In: Precancerous Conditions and Lesions of the Stomach, Zhang YC, Kawai K, eds. Berlin: Springer-Verlag, 1993: 103-20) was performed in all cases. In addition, 5[c]-exceeding events (5cEE) and the 2[c] deviation index (2cDI) were calculated, except in one histopathologically benign tumour, which revealed euploid polyploidization, as the analysis of 5cEE and 2cDI is not valid in that case.

RESULTS

A 2cDI threshold of 0.24 proved to be the most reliable marker for the distinction between malignant and benign follicular tumours. On the basis of this feature, all malignant and benign tumours were correctly classified. A specificity of 100% was achieved by all three interpretation methods, but the sensitivity of 2cDI for the detection of malignant tumours was superior to the analysis of 5cEE (sensitivity 77%) and to the stemline interpretation (sensitivity 23%).

CONCLUSIONS

DNA ICM may be helpful in distinguishing between malignant and benign follicular tumours.

DNA image cytometry on sections as compared with image cytometry on smears and flow cytometry in melanoma

DNA measurements of 130 melanomas were carried out by flow cytometry (FCM) and image cytometry (ICM). ICM was applied to cytological preparations of fresh material (cICM) and to sections of formalin-fixed paraffin embedded tissue (sICM). The DNA ploidy, the DNA index of G0/G1 peaks (DI), and the proliferation index (PI) were used to compare all the methods. The following parameters reflecting malignancy were calculated only from ICM histograms: the 5c exceeding rate (5cER) and the malignancy grade (MG). In cases found to be DNA aneuploid by FCM, the PI values (FCM versus cICM) and the DIs (between all methods) showed a high correlation, and the concordance in relation to the DNA ploidy status was 96% (FCM versus cICM) and 94% (FCM versus sICM). However, we ascertained essential differences between FCM and ICM in melanomas classified as DNA diploid by FCM. The concordance in DNA ploidy was only 66% (FCM versus cICM) and 64% (FCM versus sICM). In contrast, cICM and sICM yielded similar results in most cases. With the exception of the near diploid range, ICM is superior to FCM in detecting DNA aneuploidy. In particular, DNA tetraploid stem lines can easily be overlooked by FCM. Therefore, DNA measurements of tumours judged to be DNA diploid by FCM must be verified by ICM. ICM on sections proved to be applicable and yielded reliable results provided that a suitable thickness was used, and the measuring of sectioned and overlapping nuclei was largely avoided by careful focusing in either direction.

Image analysis in dermatopathology

BACKGROUND/AIMS

Image analysis in dermatopathology has been used for DNA ploidy analysis, morphometry, stereology, and quantitative immunohistochemistry. The object is to review image analysis in dermatopathology and evaluate these modalities and their application in pigmented lesion pathology, for elucidation of tumor behaviour and architecture and as an aid in tumor identification and prognostication.

CONCLUSION

Image analysis in dermapathology has a huge potential. The techniques are difficult and at present mainly used in specialized centres.

Differentiation between malignant melanomas and benign melanocytic nevi by computerized DNA cytometry of imprint specimens

Recently image analysis (IA) and DNA-cytophotometry (CP) have proved to be useful for the differentiation between benign and malignant melanocytic lesions on paraffin sections. Since, on sections, these procedures are very time-consuming, we tested in the present study whether IA of imprint specimens, which can be evaluated in less than 30 minutes, might also be sufficient. In 39 malignant melanomas (MM), 18 melanocytic nevi (MN), and 6 dysplastic nevi (DN), 12 different morphometric and DNA cytometric features were determined in 100 randomly selected nuclei. In univariate analysis, 5 features were found to be significantly different between the benign and malignant groups (p < 0.0001): mean value (MAREA) and standard deviation (SAREA) of nuclear area and the 80th, 90th, and 95th percentiles of DNA distribution. Using SAREA, the best univariate feature, 82.5% of the cases could be correctly separated. In multivariate analysis with a combination of three features--standard deviation of nuclear area (SAREA), mean DNA value (MDNA), and 95th percentile of DNA distribution (PERC95)--a correct diagnosis was achieved in 89.5% of the cases. Results obtained in the cases of DN indicated an increased proliferation, but did not allow the separation of DN from MM and MN. Since our technique allows a rapid analysis without loss of tissue, which might be important for histological analysis, and the classification rates are equal or still higher than reported in studies on sections, imprints of melanocytic lesions seem to be most appropriate for the calculation of DNA cytometric features as helpful diagnostic criteria in equivocal melanocytic lesions.

Image cytometry: current applications and future trends

Image cytometry has numerous clinical and research applications and is particularly useful in anatomic pathology for the study of malignant lesions. Modern image systems encompass morphometry, densitometry, neural networks, and expert systems. Rapid advances in technology and the development of user-friendly systems have provided pathologists with an alternative to flow cytometry, particularly useful in the evaluation of small or hypocellular specimens. The most common current application of image cytometry is for DNA analysis, followed by quantitation of immunohistochemical staining. Newer uses under active investigation include development of expert systems that may act as diagnostic consultants in the future. Beyond DNA analysis, image cytometry holds great promise for improved tumor classification, for screening and surveillance in high-risk populations, and as a tool to improve diagnostic ability. This article discusses types of image analysis systems, specimen preparation, data acquisition, current applications in specific organ sites, and possible future applications.

Digital imaging in dermatology

In this article we discuss the recent surge in activity in digital imaging in dermatology. The key role of digital imaging as an adjunct to detection of early malignant melanoma, with application in following patients with the dysplastic nevus syndrome, is explored. Other current and future uses of digital imaging in image archiving, in clinical studies such as hair growth studies, and in telediagnosis are reviewed. We review the varying research activities of image analysis laboratories participating in the dermatology image researching group. Research laboratories included in this group are at Oregon Health Sciences University, Xerox Corporation, University of Arizona, University of Cincinnati, University of Munich, University of Wurzburg, University of Arkansas, Harvard University, Southern Illinois University-Edwardsville, Johns Hopkins University, National Institutes of Health, and University of Missouri at Columbia and Rolla. The role of new imaging devices in dermatology including the "nevoscope" and the dermatoscope is explored. Goals and challenges for the new technology are discussed.

Ultrastructural discrimination between malignant melanomas and benign nevocytic nevi using high-resolution image and multivariate analyses

Prompted by the well-known difficulties of reliable and objective histologic differentiation between initial malignant melanoma (MM) and benign nevocytic nevi (NN), ultrastructural high-resolution image and multivariate analyses were evaluated for their diagnostic efficiency. Thirty-seven different features describing morphometry (area, circumference, and shape factor), amount of heterochromatin and euchromatin, chromatin homogeneity, and presence of smaller dark chromatin aggregations were determined by a MICROVAX 3500 computer in each of 1840 intraepidermal melanocytic nuclei of 17 MM and 20 NN. A strategy for the classification of cases based on the identification of markedly atypical melanocytic cells (MACS) was developed. MACS, selected in multivariate analysis with a linear combination of the eight most important features for cell classification, were found in 39.4% of the melanoma cells, but only in 0.3% of nevocytic nevus cells. The presence of MACS allowed a clear differentiation between MM and NN. All cases of MM had more than four MACS, whereas 17 cases of nevocytic nevi were MACS negative, and in each of the remaining three cases only one MAC was present. The percentage of MACS detected within intraepidermal parts of MM by using computerized high-resolution image analysis was found to be a highly efficient diagnostic marker. The new classification strategy has the potential of saving considerable time in subsequent studies, because preselected sampling and the calculation of only a few criteria have proven sufficient for correct classification of malignant melanomas.

Prognostic significance of DNA cytometry in cutaneous malignant lymphomas

The current classification of cutaneous malignant lymphomas (ML) into low-grade and high-grade lymphomas was found to be of limited reproducibility and permitted only a rough prediction about outcome. With this in mind, the relationship between nuclear DNA content and both prognosis and histologic grading according to the Kiel classification was evaluated on Feulgen-stained imprint specimens. In all, 49 cases of malignant non-Hodgkin's lymphoma, primary of the skin or with an involvement of the skin as one of the first symptoms, were studied using a computerized high-resolution image analysis system. The 2c deviation index (2cDI), which reflects the variation of the nuclear DNA values around the normal diploid peak, was found to be the best prognostically relevant criterion. Using the 2cDI, a significant discrimination (P less than 0.001 in the U test) between low-grade and high-grade ML was achieved. The prognostic benefit of the 2cDI was well documented by a significant inverse correlation between the 2cDI and the period of time until the patients progressed at least into one higher stage or died of lymphoma (r equals -0.63, P less than 0.05). In addition, the 2cDI enabled prognosis of the course of disease. In the group with low 2cDI values (2cDI, less than 0.5), no progression of the disease was observed after 1 year. In the groups presenting with a 2cDI between 0.5 and 1.0 and higher than 1.0, a progression was found in 57% and 64% of the cases studied, respectively. In conclusion, these measurements indicate that the determination of DNA distribution patterns in imprint specimens allows a precise and objective prognostic evaluation of cutaneous ML.

What dermatologists should know about digital imaging

The digital imaging revolution that swept other medical specialties in the late 1970s and early 1980s is beginning to find new and important roles in dermatology. This technology has a wide range of educational, clinical, and research applications. Dermatologists should understand certain basic concepts about images and imaging techniques to take advantage of progress in this field and eventually apply it to their own research and/or clinical practice.